Instructions to use nvidia/OpenMath-CodeLlama-7b-Python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/OpenMath-CodeLlama-7b-Python with NeMo:
# tag did not correspond to a valid NeMo domain.
- Notebooks
- Google Colab
- Kaggle
Download nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/13.1.0 from nvidia/OpenMath-CodeLlama-7b-Python: direct link, hf CLI and curl.
- Browser
- Download file 25.2 MB
-
https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/13.1.0
- Command line
-
hf download hf://nvidia/OpenMath-CodeLlama-7b-Python/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/13.1.0
-
curl -L -o 13.1.0 https://huggingface.co/nvidia/OpenMath-CodeLlama-7b-Python/resolve/main/nemo_model/model_weights/model.decoder.layers.self_attention.linear_qkv.weight/13.1.0
25.2 MB
- Xet hash:
- e08ec13394532293a9377b49f1374a06fa3664877bd9e1f8047bae27c0613c3a
- Size of remote file:
- 25.2 MB
- SHA256:
- 836ae2991528b160cdd15630e5f45d73583ee021aa0aee40b364c16c5b624cff
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